An Artificial Intelligence Based Approach to Automate Document Processing in Business Area

Automatic document processing is always a strategy for business executives to improve operational efficiency. With Optical Character Recognition (OCR) and machine learning techniques, businesses are able to apply Artificial Intelligence (AI) to automate the process. However, introducing an AI application to business is challenging; it is easy to fail because of the complexity between the technical and organizational components. This thesis considers document processing from a sociotechnical system perspective and leverages a four-step system analysis approach to identify the critical components. This research also proposes a machine learning model using Support Vector Machine (SVM) as the classifier and Word2vec embeddings as document features to classify business documents. The proposed model reaches a 0.872 Macro F1-score using scanned business documents from the RVL-CDIP dataset. The proposed model outperforms the other commonly used rule-based algorithms, RIPPER and PART, showing that the proposed model is potentially suitable to be deployed into business to classify the documents.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Chen, Ta Hang

Advisors dc:contributor.advisor

• Gupta, Amar
• Szolovits, Peter
• Rhodes, Donna H.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139571

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139571